Novartis Researches Novel Digital Biomarkers

May 24, 2018
Moe Alsumidaie

Applied Clinical Trials

John Reites, THREAD’s Chief Product Officer, will discuss eDROs and the FocalView App in this interview.

Innovators in the clinical trials industry are pushing the limits in an attempt to develop, use, and validate novel electronic active tasks (also known as digital reported outcomes (eDROs)), a form of a digital biomarker. Novartis is collaborating with THREAD Research to launch the FocalView application and study, with the purpose of collecting ocular disease-related eDROs from patients. John Reites, THREAD’s Chief Product Officer, will discuss eDROs and the FocalView App in this interview.

What is the FocalView app and how it is being used in clinical trials?

Novartis FocalView is an iOS app in the US app store, available for patients to directly enroll into an observational remote research study. The patient onboarding is simple in that patients download the app, go through eligibility criteria, review and provide a single signature eConsent, and begin study activities such as ePROs, surveys, and electronic device reported outcomes (eDROs). The eDROs include patient reminders, training, and assessments around visual acuity and sensitivity. As patients are engaging with the study and contributing data, they can start to see what their acuity or visual test results look like overtime. The results of these assessments not only contribute to the observational study, but could also be reviewed by the patient with their ophthalmology provider.

How will data from the FocalView app be used for digital validation?

Digital validation is a journey; you have to first develop the assessment, launch it on a wider scale, collect data, and then the assessment has the potential to become a new validated measure after it has been scientifically evaluated. Some of the eDROs that we have worked with in the past are in validation studies today in fit-for-purpose use cases. The FocalView eDROs are an innovative example of how you can use bring your own device (BYOD) capabilities via mobile to potentially create a validated measurement that can be used in clinical trials and other healthcare settings.

Is the FDA accepting the use of eDROs in clinical trial settings?

The use of active tasks or eDROs is still in its infancy in clinical research. We see eDROs being utilized in observational and post approval studies today and believe the use in clinical trials will begin to increase. As we can see from examples like the mHealth Action Plan and digital health pre-certification program supported by FDA, the agency has been open and approachable to explore the use of these new digital endpoints in research. We are excited to see these new data types gaining traction to support new endpoints with an activity-based engagement for patients.

What has been the patient's response to using FocalView?

We are excited to see the patient’s response and believe from our other remote/virtual research study experiences that a key to their satisfaction is derived when the app is fit-for-purpose (i.e., to be used specifically for that target patient population) to provide the patient value, support, and a frictionless way to collect data remotely. In order to make an app fit-for-purpose, you have to engineer it for patients to clearly understand what they are enrolling into and the purpose of data collected for research. Novartis’ FocalView app is an excellent example in the use of transparent language for the patient, helping them understand how the exams work and what data is being collected. The overall experience is customized specifically for ophthalmology patients with their needs and support in mind. This approach is strategic as we balance providing value and support to patients with being cognizant of their time required and understanding the need to capture continuous and quality data.

 

Moe Alsumidaie, MBA, MSF is Chief Data Scientist at Annex Clinical, and Editorial Advisory Board member for and regular contributor to Applied Clinical Trials.